1. Field of the Invention
The present invention generally relates to an image processing system and, more particularly, to an image data processing system for performing binary quantization of image data of a document on which different types of images, such as characters and photographs, are formed together.
2. Description of the Related Art
Recently, an image processing apparatus, such as a document image processing apparatus, capable of processing image data as well as code data has been developed. In this apparatus, image data such as document images read by a read means, e.g., a scanner, image data, such as characters and drawings having contrast are processed by simple binary quantization using a fixed threshold value, whereas image data such as photographs having gradation are subjected to gradation binary quantization by a pseudo-gradation means such as a dither method. The above methods are selectively employed for the following reasons. If image data are uniformly processed by simple binary quantization using the fixed threshold, the resolution of regions comprised of characters, drawings, and the like is preserved, and hence no degradation in image quality occurs upon image reproduction. In regions comprised of photographs and the like, however, the gradation is not preserved, and hence degradation in image quality occurs in a reproduced image. In contrast to this, if the image data is uniformly processed by gradation binary quantization using an ordered dither method or the like, the gradation of regions comprised of photographs and the like is preserved, and hence no degradation in image quality occurs upon image reproduction. In regions comprised of characters, drawings, and the like, however, the resolution is decreased, and hence degradation in image quality occurs in a reproduced image.
As described above, if binary quantization of image data is performed by one binary quantization technique, it is impossible to obtain a reproduced image which can satisfy image quality of both types of regions, i.e., a character drawings region and a photographic region. Therefore, an adaptive processing technique is indispensable for document image processing. In this technique, image data including different types of images are separated into regions in accordance with the feature of each image, and adaptive processing is performed for each region. This can be applied to other types of image processing. For example, if image processing is not performed in accordance with the feature of an image degradation in image quality occurs in enlargement/reduction processing of the binarized image. Furthermore, in a coding process, if an image is processed by a compression scheme which is not suitable for the feature of the image, data compression cannot be efficiently performed.
As disclosed in, e.g., Published Unexamined Japanese Patent Application No. 58-3374, therefore, a binary quantization system which can satisfactorily maintain both the resolution and gradation levels of character and photographic portions has been proposed. In this system, maximum density differences .DELTA.Dmax of image density in local regions on an image surface, and the maximum density differences .DELTA.Dmax are compared with a determination threshold value T so as to divide the entire image into character/drawing regions and photographic regions, thereby switching binary quantization methods in accordance with the feature of each image region. In this case, the term "density" represents the signal level of an image read by a read means and hence differs from its general meaning. The term "density" will be used in this meaning hereinafter unless otherwise specified.
In the above-described system, however, a photographic image region in which the density abruptly changes is mistaken for a character region, and as a result, the gradation is degraded upon reproduction. For example, assume that the dynamic range of an image density is constituted by 8 bits (0 to 255: 0 to FF [hex] in hexadecimal notation). In a character image, the frequency distribution of maximum density differences .DELTA.Dmax exhibits peak values near 0 [hex] and FF [hex], as shown in FIG. 12. Pixels having values close to FF [hex] are pixels including an edge portion of a character within a predetermined area. All pixels, within a predetermined area, having values close to 0 [hex] are background pixels or pixels within a character portion including no edge portion. In a photographic image, since changes in density in local regions are relatively small, the maximum density differences .DELTA.Dmax within a predetermined area are concentrated on values close to 0 [hex], as shown in FIG. 13.
Identification of image types is performed for the images having the frequency distributions of the maximum density differences .DELTA.Dmax described above by using a predetermined threshold (T=70 [hex]) under the following conditions:
(1) If .DELTA.Dmax&gt;T, a corresponding portion is identified as a character portion.
(2) If .DELTA.Dmax.ltoreq.T, a corresponding portion is identified as a photographic portion.
According to this method, when a character image is processed, it is properly determined that pixels having the maximum density differences .DELTA.Dmax in a region indicated by 1 in FIG. 12 are character pixels by condition (1). However, pixels having the maximum density differences .DELTA.Dmax in a region indicated by 2 in FIG. 12 are mistaken for pixels of a photographic graphic portion by condition (2). In contrast to this, when a photographic image is processed, it is properly determined that pixels having the maximum density differences .DELTA.Dmax in a region indicated by 4 in FIG. 13 are photographic pixels by condition (2). However, pixels having maximum density differences .DELTA.Dmax in a region indicated by 3 in FIG. 13 are mistaken for pixels of a character portion by condition (1). This determination error of the photographic image indicates that it is determined that pixels which are located in a predetermined area and exhibit an abrupt change in density, e.g., pixels of a profile portion of a face, are mistaken for character pixels. For this reason, in binary quantization, degradation in image quality of a reproduced image occurs due to degradation in gradation. Especially, in a photographic image, a whose density abruptly changes is visually conspicuous portion.
When identification of character/drawing portions and photographic portions is to be performed using the maximum density differences .DELTA.Dmax as feature amounts, since pixels located within a predetermined area and including a region whose density change is large are mistaken for pixels of a character portion, image regions cannot be accurately separated. For this reason, binary quantization cannot be adaptively and accurately performed in accordance with the feature of each image. That is, the above-described method cannot contribute to optimal reproduction of an image which satisfies both the resolution and gradation of character and photographic portions.